PM2.5 pollution is threatening human health and quality of life, especially in some densely populated regions of Asia and Africa. This paper used remotely sensed annual mean PM2.5 concentrations to explore the spatiotemporal evolution of global continental PM2.5 pollution from 2000 to 2014. The work employed an improved Bayesian space-time hierarchy model combined with a multiscale homogeneous subdivision method. The statistical results quantitatively demonstrated a ‘high-value increasing and low-value decreasing’ trend. Areas with annual PM2.5 concentrations of more than 70μg/m3 and less than 10μg/m3 expanded, while areas with of an annual PM2.5 concentrations of 10–25μg/m3 shrank. The most heavily PM2.5-polluted areas were located in northwest Africa, where the PM2.5 pollution level was 12.0 times higher than the average global continental level; parts of China represented the second most PM2.5-polluted areas, followed by northern India and Saudi Arabia and Iraq in the Middle East region. Nearly all (96.50%) of the highly PM2.5-polluted area (hot spots) had an increasing local trend, while 68.98% of the lightly PM2.5-polluted areas (cold spots) had a decreasing local trend. In contrast, 22.82% of the cold spot areas exhibited an increasing local trend. Moreover, the spatiotemporal variation in the health risk from exposure to PM2.5 over the global continents was also investigated. Four areas, India, eastern and southern China, western Africa and central Europe, had high health risks from PM2.5 exposure. Northern India, northeastern Pakistan, and mid-eastern China had not only the highest risk but also a significant increasing trend; the areas of high PM2.5 pollution risk are thus expanding, and the number of affected people is increasing. Northern and central Africa, the Arabian Peninsula, the Middle East, western Russia and central Europe also exhibited increasing PM2.5 pollution health risks.

Under the background of growing greenhouse gas emissions and the resulting global warming, researches about the spatial-temporal variation analysis of the concentration of carbon dioxide in the regional and global scale has become one of the most important topics in the scientific community. Simulating and analyzing the spatial-temporal variation of the carbon dioxide concentration on a global scale under limited observation data has become one of the key problems to be solved in the research field of spatial analysis technology. A new research approach based on high accuracy surface modeling data fusion (HASM-DF) method was proposed in this paper, in which the output of the CO2 concentration of the GEOS-Chem model were taken as driving field, and the observation values of CO2 concentration at ground observation station were taken as accuracy control conditions. The new approach's objective is to fulfill the fusion of the two kinds of CO2 data, and obtain the distribution of CO2 on a global scale with a higher accuracy than the results of GEOS-Chem. Root mean square error (RMSE) was chosen as the basic accuracy index, and the experimental analysis shows that the RMSE of the result of the proposed approach is 1.886 ppm, which is significantly lower than that of the GEOS-Chem's 2.239 ppm. Furthermore, compared with the results created by the interpolation methods used the observation values at stations; the fusion results keep a good spatial heterogeneity similar to the results of GEOS-Chem. This research analyzed the spatial distribution and time series variation of the near-surface CO2 based on the fusion result on a global scale. And it can found that areas such as East Asia, Western North American, Central South America and Central Africa and other region show a relatively high value of the near-surface CO2 concentration. And we also found that the near-surface CO2 concentration changes with season, especially in North America and Eurasia, the near-surface CO2 in summer was significantly lower than winter in these areas.

Due to the development of the metallurgical and energy industries and the operation of incinerators, more and more environmental pollution is occurring. Toxic elements accumulate in the biosphere and affect the state of the population of the regions of large-scale production or the disposal of industrial waste. The main goal of this study was to compare the toxic elements hair composition in people from different regions of the world. The concentrations of toxic and potentially toxic elements (Al, As, Be, Cd, Hg, Pb, Sn) in 198 people, first-year students of People’s Friendship University of Russia, who arrived from different regions of the world, were measured with inductively coupled plasma mass spectrometry. Students were divided into 6 groups: from South and East Asia, from Latin America, from Arab countries, Central Asia and Afghanistan, from South and Central Africa, from Iran and Azerbaijan, and from Russia, Ukraine, and Moldova. Medians of the concentrations of elements in the hair in the general group were 5.8 μg/g for Al, 30 ng/g for As, 0.6 ng/g for Be, 9.0 ng/g for Cd, 0.11 μg/g for Hg, 0.24 μg/g for Pb, and 0.11 μg/g for Sn. All these values fall within the normal range. Students from Russia, Moldova, and Ukraine showed a significantly higher Sn content (0.28 μg/g) in their hair than subjects from other regions except for Latin America, p<0,05. Except for As, cases of exceeding their recommended concentrations in the hair were identified. However, the proportion of subjects with deviations in each group was not high — not more than 7%. In all regions, a positive correlation was found between Cd, Pb, and Sn, p<0.05, r>0.5 for all. Cases of exceeding the maximum permissible concentrations of various toxic elements in the hair were detected in people from all regions of the Earth included in the study. And although the overall picture of the content of toxic elements in the hair of students from all regions in our study does not look critical, the results of previous studies, as well as information about the total deterioration of the environmental situation throughout the Earth, necessitate further large-scale environmental studies.

Climate scenarios for future global warming expect the enhancement of the hydrological cycle during the twenty-first century. In particular, accurate simulation of water content in the soil depends not only on the correct determination of the percentages of each component in the water balance but also on the measured biophysical properties of the soil available. One of the greatest man-made environmental disasters in history is the destruction of the Aral Sea which is heavily polluted. Possible scenarios have been formulated, to transfer water from the Siberian rivers to Central Asia and to limit the unsustainable extension of irrigation in this region. A new scenario proposed in this paper is partly based on the use of Caspian water evaporators located on the eastern coast of the Caspian Sea. The implementation of this scenario allows the rescue of the Aral Sea and the normalization of water balance in Central Asia. The results of the calculations show that the Aral Sea can be restored over the next 90–240 years depending on these versions. If the anthropogenic outflow of river water is further reduced by 10%, the Aral Sea will be restored for about 90 years. Finally, possible versions of the water recovery scenario are discussed and evaluated and compared with other examples such as Lake Eyre in Australia, Lake Sevan in Armenia, and Lake Chad in central Africa.

6 pages | International audience | To better understand the Central Africa forests sensitivity toclimate variability, we jointly analyse the mean annual cycles of greenness, rainfall, cloudiness and solarradiation for the target region 0-5°N/12-19°E using high resolution satellite data. Our results demonstrate theimportance of the diurnal scale for understanding the mean annual cycles of rainfall, cloudiness and solarradiation and the way they shape those of forest greenness. They also suggest that whereas the March-Mayrainy season appears optimal for greenness especially because of favorable light conditions, water availabilityis the main controlling factor in December-January the main dry season and in February at the start of the firstvegetative season. Regarding the little dry season and the second rainy season (July-October) light availabilitymight be the main limiting factor to forests photosynthetic activity. | Afin de mieux comprendre la sensibilité de la forêt d'Afrique Centrale à la variabilité climatiqueactuelle, une analyse détaillée des cycles saisonniers moyens d'activité photosynthétique, de précipitations, decouverture nuageuse et de radiation solaire est menée pour la région 0-5°N/12-19°E, en s'appuyant sur desobservations satellites haute résolution spatiale et temporelle. Nos résultats montrent tout d'abord que l'échellediurne est une échelle clé pour comprendre les cycles saisonniers moyens de précipitations, nébulosité etradiation solaire, et comment ils façonnent celui d'activité photosynthétique des forêts. Ensuite, alors que lasaison mars-mai semble optimale pour l'activité photosynthétique des forêts en raison d'une bonne disponibilitéen lumière, la disponibilité en eau est le facteur de contrôle principal durant la grande saison sèche (décembrejanvier)et au démarrage de la 1ère saison végétative (février). De juillet à octobre, la plus faible disponibilitéen lumière pourrait être le principal facteur explicatif à la baisse de l'activité photosynthétique.